DBMS > Google BigQuery vs. JaguarDB vs. Microsoft Azure Table Storage vs. SQLite

System Properties Comparison Google BigQuery vs. JaguarDB vs. Microsoft Azure Table Storage vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Performant, highly scalable DBMS for AI and IoT applications

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used embeddable, in-process RDBMS

Primary database model

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	36.00
Rank	#24	Overall
	#15	Relational DBMS

Score	0.05
Rank	#313	Overall
	#49	Key-value stores

Score	5.28
Rank	#70	Overall
	#5	Wide column stores

Score	121.89
Rank	#9	Overall
	#6	Relational DBMS

Website

cloud.google.com/bigquery

www.datajaguar.com

azure.microsoft.com/en-us/services/storage/tables

www.sqlite.org

Technical documentation

cloud.google.com/bigquery/docs

www.datajaguar.com/support.php

www.sqlite.org/docs.html

Developer

Google

DataJaguar, Inc.

Microsoft

Dwayne Richard Hipp

Initial release

2010

2015

2012

2000

Current release

2.9.4 September 2018

3.34.0 (December 1, 2020), December 2020

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

the server part. Clients available in other languages

Server operating systems

hosted

Linux

hosted

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access privileges (owner, writer, reader) for whole datasets, not for individual tables

Google Cloud Identity & Access Management (IAM)

rights management via user accounts

Access rights based on private key authentication or shared access signatures

More information provided by the system vendor

Specific characteristics

SQL support, group by, order by, join
» more

Competitive advantages

Extremely easy to scale-out (in seconds) 100,000 times faster
» more

Typical application scenarios

IoT data, time series data, AI data. Any type of numerical data.
» more

Key customers

Quantea, 2PiDay, Synqy, SinoLogistics, IIVI
» more

Market metrics

Advertising awareness, installed base, brand image, market share
» more

Licensing and pricing models

Free-trial license, per-node license, and subscription license.
» more

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